---------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\sbstjp\OneDrive - Cardiff University\FinalHarvard\Appendix8.2.log
  log type:  text
 opened on:  12 May 2025, 18:06:25

. use "C:\Users\sbstjp\OneDrive - Cardiff University\anes_timeseries_2024_stata_20250219.dta" // ANES 2024 Time
>  Series Study // Preliminary Release: Pre-Election Data February 19, 2025 version

. 
. // Create social justice scale
. * Rename variables 
. rename V241290x Edi 

. rename V241372x Tgbathroom 

. rename V241375x Tgsport 

. rename V241412x Appprotestgaza 

. 
. * Delete missing values
. foreach var in Edi Tgbathroom Tgsport Appprotestgaza {
  2.     replace `var' = . if `var' < 0
  3.     tabulate `var', missing
  4. }
(308 real changes made, 308 to missing)

PRE: SUMMARY Approve/disapprove |
         Diversity, Equity, and |
                Inclusion (DEI) |      Freq.     Percent        Cum.
--------------------------------+-----------------------------------
          1. Favor a great deal |        427       12.75       12.75
     2. Favor a moderate amount |        465       13.88       26.63
              3. Favor a little |        147        4.39       31.02
    4. Neither favor nor oppose |      1,129       33.71       64.74
             5. Oppose a little |         99        2.96       67.69
    6. Oppose a moderate amount |        272        8.12       75.81
         7. Oppose a great deal |        502       14.99       90.80
                              . |        308        9.20      100.00
--------------------------------+-----------------------------------
                          Total |      3,349      100.00
(278 real changes made, 278 to missing)

                  PRE: SUMMARY: |
 Approve/disapprove transgender |
       people use bathroom that |
                     matches ge |      Freq.     Percent        Cum.
--------------------------------+-----------------------------------
          1. Favor a great deal |        486       14.51       14.51
     2. Favor a moderate amount |        274        8.18       22.69
              3. Favor a little |         97        2.90       25.59
    4. Neither favor nor oppose |        744       22.22       47.81
             5. Oppose a little |         75        2.24       50.04
    6. Oppose a moderate amount |        219        6.54       56.58
         7. Oppose a great deal |      1,176       35.11       91.70
                              . |        278        8.30      100.00
--------------------------------+-----------------------------------
                          Total |      3,349      100.00
(277 real changes made, 277 to missing)

     PRE: SUMMARY: Favor/oppose |
 banning transgender girls from |
              K-12 girls sports |      Freq.     Percent        Cum.
--------------------------------+-----------------------------------
          1. Favor a great deal |      1,127       33.65       33.65
     2. Favor a moderate amount |        254        7.58       41.24
              3. Favor a little |         95        2.84       44.07
    4. Neither favor nor oppose |        814       24.31       68.38
             5. Oppose a little |         78        2.33       70.71
    6. Oppose a moderate amount |        243        7.26       77.96
         7. Oppose a great deal |        461       13.77       91.73
                              . |        277        8.27      100.00
--------------------------------+-----------------------------------
                          Total |      3,349      100.00
(288 real changes made, 288 to missing)

    PRE: SUMMARY: Approve/disapprove of |
           protests against war in Gaza |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
           1. Approve a lot of protests |        278        8.30        8.30
2. Approve a moderate amount of protest |        298        8.90       17.20
        3. Approve a little of protests |        136        4.06       21.26
4. Neither approve nor disapprove of pr |      1,135       33.89       55.15
     5. Disapprove a little of protests |        129        3.85       59.00
6. Disapprove a moderate amount of prot |        335       10.00       69.01
        7. Disapprove a lot of protests |        750       22.39       91.40
                                      . |        288        8.60      100.00
----------------------------------------+-----------------------------------
                                  Total |      3,349      100.00

. 
. *Reverse coding so social justice values are high
. foreach var in Appprotestgaza Tgbathroom Edi {
  2.     qui sum `var'
  3.     local max_value = r(max)
  4.     gen r`var' = `max_value' + 1 - `var'
  5. }
(288 missing values generated)
(278 missing values generated)
(308 missing values generated)

. 
. *Standardize items in the scale from 1-2 - this avoids 0, for reasons outlined in next step
. foreach var in rEdi rTgbathroom Tgsport rAppprotestgaza {
  2.     summarize `var'
  3.     gen s`var' = 1 + (`var' - r(min)) / (r(max) - r(min))
  4. }

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        rEdi |      3,041    4.068727      1.9484          1          7
(308 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 rTgbathroom |      3,071    3.368935    2.274272          1          7
(278 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     Tgsport |      3,072    3.336914    2.217592          1          7
(277 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
rAppprotes~a |      3,061    3.515518    1.924261          1          7
(288 missing values generated)

. 
. *At this point, the scale has a Cronbach's alpha of 0.76. 
. 
. * Replace missing values with 0 for the specified variables - this is necessary as Stata doesn't add up missi
> ng values and means a 0-1 standardization scale isn't feasible as missing values would overlap with the scale
. foreach var in srEdi srTgbathroom sTgsport srAppprotestgaza {
  2.     replace `var' = 0 if missing(`var')
  3. }
(308 real changes made)
(278 real changes made)
(277 real changes made)
(288 real changes made)

. 
. * Initialize the total score and the count of non-zero responses
. gen total_scoreSJV = 0

. gen count_nonzeroSJV = 0

. 
. * Add each variable to the total scale score and count it if non-zero
. foreach var in srEdi srTgbathroom sTgsport srAppprotestgaza  {
  2.     replace total_scoreSJV = total_scoreSJV + `var'
  3.     replace count_nonzeroSJV = count_nonzeroSJV + (`var' != 0)
  4. }
(3,041 real changes made)
(3,041 real changes made)
(3,071 real changes made)
(3,071 real changes made)
(3,072 real changes made)
(3,072 real changes made)
(3,061 real changes made)
(3,061 real changes made)

. 
. * Calculate the average score, avoiding division by zero
. gen SocJusValues = .
(3,349 missing values generated)

. replace SocJusValues = total_scoreSJV / count_nonzeroSJV if count_nonzeroSJV > 0
(3,097 real changes made)

. 
. // Liberalism scale
. * Rename
. rename V241269x bordersecurity

. rename V241302 abortion

. rename V241272x crime

. rename V241308x deathpenalty

. rename V241395x wall

. rename V241389x birthrightcit

. rename V241381x gayadoption

. rename V241258 environment

. 
. *Drop missing values
. foreach var in gayadoption bordersecurity crime deathpenalty wall birthrightcit {
  2.     replace `var' = . if inlist(`var', -1, -2)
  3. }
(322 real changes made, 322 to missing)
(269 real changes made, 269 to missing)
(264 real changes made, 264 to missing)
(319 real changes made, 319 to missing)
(266 real changes made, 266 to missing)
(269 real changes made, 269 to missing)

. 
. replace abortion = . if inlist(abortion, -9, -8, -1, 5)   
(377 real changes made, 377 to missing)

. replace environment = . if inlist(environment, -9, -8, -1, 99)  
(722 real changes made, 722 to missing)

. 
. *Reverse code so liberal values are high
. foreach var in gayadoption environment {
  2.     qui sum `var'
  3.     local max_value = r(max)
  4.     gen r`var' = `max_value' + 1 - `var'
  5. }
(322 missing values generated)
(722 missing values generated)

.  
. *Standardize items in the scale from 1-2 - this avoids 0, for reasons outlined in next step
. foreach var in bordersecurity abortion crime deathpenalty wall birthrightcit rgayadoption renvironment {
  2.     summarize `var'
  3.     gen s`var' = 1 + (`var' - r(min)) / (r(max) - r(min))
  4. }

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
bordersecu~y |      3,080    1.963961    1.158024          1          5
(269 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
    abortion |      2,972    3.145693    .9763123          1          4
(377 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
       crime |      3,085    2.023663    1.064897          1          5
(264 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
deathpenalty |      3,030    2.167327    1.139084          1          4
(319 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        wall |      3,083    3.748621    2.345843          1          7
(266 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
birthright~t |      3,080    4.441558    2.129723          1          7
(269 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
rgayadoption |      3,027    4.677569    1.768987          1          6
(322 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
renvironment |      2,627    4.839741    1.947476          1          7
(722 missing values generated)

. 
. * Replace missing values with 0 for the specified variables - this is necessary as Stata doesn't add up missi
> ng values and means a 0-1 standardization scale isn't feasible as missing values would overlap with the scale
. foreach var in sbordersecurity sabortion scrime sdeathpenalty swall sbirthrightcit srgayadoption srenvironmen
> t {
  2.     replace `var' = 0 if missing(`var')
  3. }
(269 real changes made)
(377 real changes made)
(264 real changes made)
(319 real changes made)
(266 real changes made)
(269 real changes made)
(322 real changes made)
(722 real changes made)

. 
. * Initialize the total score and the count of non-zero responses
. gen total_scoreAL = 0

. gen count_nonzeroAL = 0

. 
. * Add each variable to the total scale score and count it if non-zero
. foreach var in sbordersecurity sabortion scrime sdeathpenalty swall sbirthrightcit srgayadoption srenvironmen
> t {
  2.     replace total_scoreAL = total_scoreAL + `var'
  3.     replace count_nonzeroAL = count_nonzeroAL + (`var' != 0)
  4. }
(3,080 real changes made)
(3,080 real changes made)
(2,972 real changes made)
(2,972 real changes made)
(3,085 real changes made)
(3,085 real changes made)
(3,030 real changes made)
(3,030 real changes made)
(3,083 real changes made)
(3,083 real changes made)
(3,080 real changes made)
(3,080 real changes made)
(3,027 real changes made)
(3,027 real changes made)
(2,627 real changes made)
(2,627 real changes made)

. 
. * Calculate the average score, avoiding division by zero
. gen LibValues = .
(3,349 missing values generated)

. replace LibValues = total_scoreAL / count_nonzeroAL if count_nonzeroAL > 0
(3,102 real changes made)

. 
. // Demographics
. *Delete missing values and rename
. rename V241458x age

. replace age=. if age<0 
(175 real changes made, 175 to missing)

. 
. rename V241566x income

. replace income=. if income<0 
(437 real changes made, 437 to missing)

. 
. replace V241177=. if V241177==99 
(542 real changes made, 542 to missing)

. replace V241177=. if V241177<0
(24 real changes made, 24 to missing)

. rename V241177 libconsp

. 
. * Generate dummies
. gen FemaleGender=.
(3,349 missing values generated)

. replace FemaleGender=1 if V241551==1
(1,416 real changes made)

. replace FemaleGender=2 if V241551==2
(1,612 real changes made)

. 
. gen Graduate=.
(3,349 missing values generated)

. replace Graduate=0 if inrange(V241465x, 1, 3)
(1,895 real changes made)

. replace Graduate=1 if inlist(V241465x, 4, 5)
(1,403 real changes made)

. 
. gen BIPOC=.
(3,349 missing values generated)

. replace BIPOC=0 if V241501x==1
(2,301 real changes made)

. replace BIPOC=1 if inrange(V241501x, 2, 6)
(1,001 real changes made)

. 
. // Standardize 
. egen Age = std(age)
(175 missing values generated)

. egen Income = std(income)
(437 missing values generated)

. 
. // Democratic questions
. replace V241324=. if V241324<0
(273 real changes made, 273 to missing)

. replace V241325=. if V241325<0
(271 real changes made, 271 to missing)

. 
. *Standardize items in the scale from 1-2, so coefficients can be compared to others in book
. foreach var in V241324 V241325 {
  2.     summarize `var'
  3.     gen s`var' = 1 + (`var' - r(min)) / (r(max) - r(min))
  4. }

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     V241324 |      3,076    3.660923    1.321657          1          5
(273 missing values generated)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     V241325 |      3,078    4.303119    .9388502          1          5
(271 missing values generated)

. 
. rename sV241324 NewsOrgs

. rename sV241325 BranchesOfGov

. 
. // Regressions
. regress NewsOrgs LibValues [pweight=V240105a], robust 
(sum of wgt is 3,131.52451586501)

Linear regression                               Number of obs     =      3,076
                                                F(1, 3074)        =      83.34
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0473
                                                Root MSE          =     .32017

------------------------------------------------------------------------------
             |               Robust
    NewsOrgs | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   LibValues |   .3313967    .036302     9.13   0.000     .2602181    .4025753
       _cons |   1.163958   .0557419    20.88   0.000     1.054663    1.273253
------------------------------------------------------------------------------

. eststo
(est1 stored)

. regress NewsOrgs LibValues Age BIPOC FemaleGender Graduate Income [pweight=V240105a], robust 
(sum of wgt is 2,785.04471336646)

Linear regression                               Number of obs     =      2,719
                                                F(6, 2712)        =      48.59
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1397
                                                Root MSE          =     .30506

------------------------------------------------------------------------------
             |               Robust
    NewsOrgs | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   LibValues |   .3352503   .0376829     8.90   0.000     .2613601    .4091404
         Age |   .0375423   .0083761     4.48   0.000     .0211182    .0539664
       BIPOC |  -.0460467   .0191202    -2.41   0.016    -.0835384   -.0085551
FemaleGender |  -.1352868   .0169878    -7.96   0.000    -.1685972   -.1019764
    Graduate |   .0976757   .0179607     5.44   0.000     .0624576    .1328938
      Income |   .0234267   .0098217     2.39   0.017     .0041679    .0426856
       _cons |   1.344974   .0627965    21.42   0.000      1.22184    1.468108
------------------------------------------------------------------------------

. eststo
(est2 stored)

. regress NewsOrgs SocJusValues [pweight=V240105a], robust 
(sum of wgt is 3,128.67985391971)

Linear regression                               Number of obs     =      3,074
                                                F(1, 3072)        =      52.46
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0291
                                                Root MSE          =     .32301

------------------------------------------------------------------------------
             |               Robust
    NewsOrgs | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
SocJusValues |   .2083999   .0287731     7.24   0.000     .1519834    .2648163
       _cons |   1.364757   .0424625    32.14   0.000     1.281499    1.448015
------------------------------------------------------------------------------

. eststo
(est3 stored)

. regress NewsOrgs SocJusValues Age BIPOC FemaleGender Graduate Income [pweight=V240105a], robust  
(sum of wgt is 2,783.02447551785)

Linear regression                               Number of obs     =      2,718
                                                F(6, 2711)        =      40.46
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1235
                                                Root MSE          =     .30785

------------------------------------------------------------------------------
             |               Robust
    NewsOrgs | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
SocJusValues |   .2089579   .0308698     6.77   0.000     .1484272    .2694886
         Age |   .0315722   .0084591     3.73   0.000     .0149853    .0481591
       BIPOC |  -.0438082   .0194003    -2.26   0.024     -.081849   -.0057674
FemaleGender |  -.1325311   .0173846    -7.62   0.000    -.1666195   -.0984426
    Graduate |   .1064026   .0185922     5.72   0.000     .0699464    .1428589
      Income |   .0305481   .0100572     3.04   0.002     .0108276    .0502686
       _cons |    1.53945   .0488539    31.51   0.000     1.443655    1.635245
------------------------------------------------------------------------------

. eststo
(est4 stored)

. regress NewsOrgs LibValues SocJusValues Age BIPOC FemaleGender Graduate Income [pweight=V240105a], robust 
(sum of wgt is 2,783.02447551785)

Linear regression                               Number of obs     =      2,718
                                                F(7, 2710)        =      41.74
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1396
                                                Root MSE          =     .30507

------------------------------------------------------------------------------
             |               Robust
    NewsOrgs | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   LibValues |   .3083867   .0649673     4.75   0.000     .1809962    .4357772
SocJusValues |   .0298702    .051914     0.58   0.565    -.0719248    .1316653
         Age |   .0375878    .008381     4.48   0.000      .021154    .0540217
       BIPOC |  -.0459998   .0192027    -2.40   0.017    -.0836532   -.0083465
FemaleGender |  -.1353194   .0170877    -7.92   0.000    -.1688256   -.1018132
    Graduate |   .0959501   .0180921     5.30   0.000     .0604745    .1314258
      Income |   .0244069   .0099955     2.44   0.015     .0048073    .0440066
       _cons |   1.343298   .0627726    21.40   0.000     1.220211    1.466385
------------------------------------------------------------------------------

. eststo
(est5 stored)

. esttab

--------------------------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)             (5)   
                 NewsOrgs        NewsOrgs        NewsOrgs        NewsOrgs        NewsOrgs   
--------------------------------------------------------------------------------------------
LibValues           0.331***        0.335***                                        0.308***
                   (9.13)          (8.90)                                          (4.75)   

Age                                0.0375***                       0.0316***       0.0376***
                                   (4.48)                          (3.73)          (4.48)   

BIPOC                             -0.0460*                        -0.0438*        -0.0460*  
                                  (-2.41)                         (-2.26)         (-2.40)   

FemaleGender                       -0.135***                       -0.133***       -0.135***
                                  (-7.96)                         (-7.62)         (-7.92)   

Graduate                           0.0977***                        0.106***       0.0960***
                                   (5.44)                          (5.72)          (5.30)   

Income                             0.0234*                         0.0305**        0.0244*  
                                   (2.39)                          (3.04)          (2.44)   

SocJusValues                                        0.208***        0.209***       0.0299   
                                                   (7.24)          (6.77)          (0.58)   

_cons               1.164***        1.345***        1.365***        1.539***        1.343***
                  (20.88)         (21.42)         (32.14)         (31.51)         (21.40)   
--------------------------------------------------------------------------------------------
N                    3076            2719            3074            2718            2718   
--------------------------------------------------------------------------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001

. 
. eststo clear

. 
. regress BranchesOfGov LibValues [pweight=V240105a], robust 
(sum of wgt is 3,128.43204482542)

Linear regression                               Number of obs     =      3,078
                                                F(1, 3076)        =      33.24
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0141
                                                Root MSE          =     .23326

------------------------------------------------------------------------------
             |               Robust
BranchesOf~v | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   LibValues |   .1294745   .0224573     5.77   0.000     .0854417    .1735072
       _cons |   1.628727   .0348363    46.75   0.000     1.560423    1.697032
------------------------------------------------------------------------------

. eststo
(est1 stored)

. regress BranchesOfGov LibValues Age BIPOC FemaleGender Graduate Income [pweight=V240105a], robust 
(sum of wgt is 2,787.19944218094)

Linear regression                               Number of obs     =      2,721
                                                F(6, 2714)        =      34.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1185
                                                Root MSE          =     .21875

------------------------------------------------------------------------------
             |               Robust
BranchesOf~v | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   LibValues |   .0978472   .0256986     3.81   0.000     .0474563    .1482381
         Age |   .0264329   .0063016     4.19   0.000     .0140765    .0387894
       BIPOC |  -.0576779   .0136836    -4.22   0.000    -.0845093   -.0308466
FemaleGender |  -.0474368   .0121235    -3.91   0.000    -.0712089   -.0236646
    Graduate |   .0729397   .0121339     6.01   0.000     .0491471    .0967322
      Income |    .039913   .0074497     5.36   0.000     .0253053    .0545207
       _cons |   1.733069   .0402775    43.03   0.000     1.654091    1.812046
------------------------------------------------------------------------------

. eststo
(est2 stored)

. regress BranchesOfGov SocJusValues [pweight=V240105a], robust 
(sum of wgt is 3,125.15916082637)

Linear regression                               Number of obs     =      3,076
                                                F(1, 3074)        =       5.00
                                                Prob > F          =     0.0254
                                                R-squared         =     0.0023
                                                Root MSE          =     .23415

------------------------------------------------------------------------------
             |               Robust
BranchesOf~v | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
SocJusValues |   .0421489   .0188466     2.24   0.025     .0051957    .0791021
       _cons |    1.76326   .0276755    63.71   0.000     1.708996    1.817525
------------------------------------------------------------------------------

. eststo
(est3 stored)

. regress BranchesOfGov SocJusValues Age BIPOC FemaleGender Graduate Income [pweight=V240105a], robust 
(sum of wgt is 2,783.92655818189)

Linear regression                               Number of obs     =      2,719
                                                F(6, 2712)        =      30.96
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1125
                                                Root MSE          =     .21896

------------------------------------------------------------------------------
             |               Robust
BranchesOf~v | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
SocJusValues |   .0282117    .021174     1.33   0.183    -.0133072    .0697306
         Age |   .0237985   .0063315     3.76   0.000     .0113835    .0362134
       BIPOC |  -.0548872   .0137165    -4.00   0.000     -.081783   -.0279914
FemaleGender |  -.0447282   .0122033    -3.67   0.000     -.068657   -.0207994
    Graduate |   .0806827   .0124549     6.48   0.000     .0562606    .1051047
      Income |   .0410301   .0074744     5.49   0.000      .026374    .0556861
       _cons |   1.831326   .0329132    55.64   0.000     1.766788    1.895863
------------------------------------------------------------------------------

. eststo
(est4 stored)

. regress BranchesOfGov LibValues SocJusValues Age BIPOC FemaleGender Graduate Income [pweight=V240105a], robus
> t 
(sum of wgt is 2,783.92655818189)

Linear regression                               Number of obs     =      2,719
                                                F(7, 2711)        =      29.39
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1205
                                                Root MSE          =     .21802

------------------------------------------------------------------------------
             |               Robust
BranchesOf~v | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   LibValues |   .1537574    .043013     3.57   0.000     .0694158     .238099
SocJusValues |  -.0610802   .0351405    -1.74   0.082     -.129985    .0078247
         Age |   .0268277   .0062787     4.27   0.000     .0145162    .0391392
       BIPOC |   -.055976   .0136043    -4.11   0.000     -.082652   -.0293001
FemaleGender |  -.0462173   .0121075    -3.82   0.000    -.0699583   -.0224764
    Graduate |   .0754101   .0122562     6.15   0.000     .0513777    .0994425
      Income |   .0379235   .0075508     5.02   0.000     .0231177    .0527294
       _cons |    1.73373   .0402107    43.12   0.000     1.654884    1.812577
------------------------------------------------------------------------------

. eststo
(est5 stored)

. esttab

--------------------------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)             (5)   
             BranchesOf~v    BranchesOf~v    BranchesOf~v    BranchesOf~v    BranchesOf~v   
--------------------------------------------------------------------------------------------
LibValues           0.129***       0.0978***                                        0.154***
                   (5.77)          (3.81)                                          (3.57)   

Age                                0.0264***                       0.0238***       0.0268***
                                   (4.19)                          (3.76)          (4.27)   

BIPOC                             -0.0577***                      -0.0549***      -0.0560***
                                  (-4.22)                         (-4.00)         (-4.11)   

FemaleGender                      -0.0474***                      -0.0447***      -0.0462***
                                  (-3.91)                         (-3.67)         (-3.82)   

Graduate                           0.0729***                       0.0807***       0.0754***
                                   (6.01)                          (6.48)          (6.15)   

Income                             0.0399***                       0.0410***       0.0379***
                                   (5.36)                          (5.49)          (5.02)   

SocJusValues                                       0.0421*         0.0282         -0.0611   
                                                   (2.24)          (1.33)         (-1.74)   

_cons               1.629***        1.733***        1.763***        1.831***        1.734***
                  (46.75)         (43.03)         (63.71)         (55.64)         (43.12)   
--------------------------------------------------------------------------------------------
N                    3078            2721            3076            2719            2719   
--------------------------------------------------------------------------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001

. 
. log close
      name:  <unnamed>
       log:  C:\Users\sbstjp\OneDrive - Cardiff University\FinalHarvard\Appendix8.2.log
  log type:  text
 closed on:  12 May 2025, 18:06:36
---------------------------------------------------------------------------------------------------------------
